Computer Security
18 papers with code • 1 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Computer Security
| Trend | Dataset | Best Model | Paper | Code | Compare |
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Libraries
Use these libraries to find Computer Security models and implementations
BIG-bench
OllaBench v.0.2
Most implemented papers
Novel Feature Extraction, Selection and Fusion for Effective Malware Family Classification
This paradigm is presented and discussed in the present paper, where emphasis has been given to the phases related to the extraction, and selection of a set of novel features for the effective representation of malware samples.
Defending Against Neural Fake News
rowanz/grover
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NeurIPS 2019
We find that best current discriminators can classify neural fake news from real, human-written, news with 73% accuracy, assuming access to a moderate level of training data.
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.
Reservoir of Diverse Adaptive Learners and Stacking Fast Hoeffding Drift Detection Methods for Evolving Data Streams
In addition, a number of methods have been developed to detect concept drifts in these streams.
Active Anomaly Detection via Ensembles
First, we present an important insight into how anomaly detector ensembles are naturally suited for active learning.
Effectiveness of Tree-based Ensembles for Anomaly Discovery: Insights, Batch and Streaming Active Learning
Our results show that active learning allows us to discover significantly more anomalies than state-of-the-art unsupervised baselines, our batch active learning algorithm discovers diverse anomalies, and our algorithms under the streaming-data setup are competitive with the batch setup.
Evaluating Explanation Methods for Deep Learning in Security
alewarne/Layerwise-Relevance-Propagation-for-LSTMs
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Deep learning is increasingly used as a building block of security systems.
Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection
Large Language Models (LLMs) are increasingly being integrated into various applications.
Neural Network-based Graph Embedding for Cross-Platform Binary Code Similarity Detection
xiaojunxu/dnn-binary-code-similarity
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The problem of cross-platform binary code similarity detection aims at detecting whether two binary functions coming from different platforms are similar or not.
Robust Neural Malware Detection Models for Emulation Sequence Learning
These models target the core of the malicious operation by learning the presence and pattern of co-occurrence of malicious event actions from within these sequences.
